A Poisson autoregressive model to understand COVID-19 contagion dynamics
Arianna Agosto and
Paolo Giudici ()
No 185, DEM Working Papers Series from University of Pavia, Department of Economics and Management
We present a statistical model which can be employed to understand the contagion dynamics of the COVID-19. The model is a Poisson autoregression, and can reveal whether contagion has a trend, and where is each country on that trend. Model results are presented from the observed series of China, Iran, Italy and South Korea.
New Economics Papers: this item is included in nep-cna and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4) Track citations by RSS feed
Downloads: (external link)
Journal Article: A Poisson Autoregressive Model to Understand COVID-19 Contagion Dynamics (2020)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:pav:demwpp:demwp0185
Access Statistics for this paper
More papers in DEM Working Papers Series from University of Pavia, Department of Economics and Management Contact information at EDIRC.
Bibliographic data for series maintained by Alice Albonico ( this e-mail address is bad, please contact ).